code: def convert_sklearn_baggind_model(operator, device, extra_config):
      assert operator is not None, "Cannot convert None operator"
  
      n_executors = operator.raw_operator.n_estimators
      is_classifier = (
          operator.raw_operator._estimator_type == "classifier"
      )
      classes = [0]
      if is_classifier:
          classes = operator.raw_operator.classes_
  
      return Bagging(operator, is_classifier, n_executors, classes)
  
file_path: hummingbird/hummingbird/ml/operator_converters/sklearn/bagging.py
imports: from packaging.version import Version, parse
  import numpy
  from onnxconverter_common.registration import register_converter
  import torch
  from .._physical_operator import PhysicalOperator
label_desc: Use image node_id 1 for calling a global function with example usage: convert_sklearn_baggind_model(operator, device, extra_config) and returns: Bagging